The Importance of Real-Time Continuous Glucose Monitoring
Real-time continuous glucose monitoring (rtCGM) has evolved over the past 15 years into a cornerstone of diabetes management. As of early 2025, approximately 10 million people worldwide use a CGM system [1].
Global annual sales reached about 10 billion USD in 2024, with strong growth (for comparison: SMBG approx. 1.7 billion USD and steadily declining) [1].
CGM systems can be used in different ways:
Several AID systems from different manufacturers are now available on the market.
Expanded Capabilities: Use in Diabetes Therapy
Ongoing improvements in measurement accuracy, ease of use, and wearing comfort have greatly broadened the clinical applications of CGM—up to its integration into fully automated insulin delivery systems.
(See Fig. SK 8 for an overview of application areas.)
rtCGM systems enable:
Provided that sensors are factory-calibrated, they can substitute for most blood glucose measurements.
Although sensors need to be replaced every 7–14 days, this is far less burdensome for patients than performing 4–7 fingersticks per day.
(However, rtCGM data should be verified with SMBG when glucose trends are unclear.)
Thus, factory-calibrated sensors closely meet patients’ desire to “avoid fingersticks.”
Patients receive real-time feedback on the effects of meals and physical activity, helping them make informed therapeutic decisions.
Particularly valuable for insulin-treated patients:
CGM is an essential technical component and a fundamental prerequisite for AID systems (automated insulin delivery).
CGM provides entirely new insights into glucose metabolism and its assessment—far beyond what SMBG can offer.
Provided the necessary interoperability standards are met, CGM data can be integrated with:
CGM enables:
Expansion of Indications for rtCGM
In Germany, based on the Federal Joint Committee (G-BA) decision of June 16, 2016, rtCGM can be prescribed for all patients on intensified insulin therapy (ICT) or insulin pump therapy [2].
Experience with CGM has revealed further benefits:
CGM can detect unphysiological and rapid glucose excursions early.
Intermittent CGM can provide “biofeedback” that helps patients adjust their lifestyle, with the potential to:
CGM is highly beneficial during patient education sessions, helping individuals visualize how meals and physical activity affect glucose levels.
This can be a powerful motivator for lifestyle changes [3].
Such use requires cooperation between the patient and the diabetes care team.
Conclusion
CGM has become a central tool in the ongoing development of diabetes management, supporting both therapeutic decisions and patient empowerment.
Fig. SK 8: Influence of rtCGM on Diabetes Therapy, Diabetes Management, and the Assessment of Glucose Data
What Can a Continuous Glucose Monitoring (CGM) System Do?
Although CGM is, at its core, “just” a measurement method, it has revolutionized diabetes management and diabetes therapy to a remarkable degree. A crucial prerequisite for this was achieving sufficient measurement accuracy.
Initially, the main focus was on gaining detailed insights into glucose regulation. This was only possible to a very limited extent with point-in-time blood glucose measurements (SMBG). Even 7 or more SMBG measurements per day cannot provide a complete picture.
Another major interest from the beginning was assessing overall metabolic control—especially the prevention of hypoglycemia. With SMBG, hypoglycemia can only be assessed to a limited degree. If a patient does not happen to measure during a low-glucose episode, detecting hypoglycemia requires that the patient notices it—i.e., the hypoglycemia must be symptomatic. It is also uncertain whether SMBG captures the lowest glucose value and impossible to determine the duration and severity of the low.
CGM completely overcomes these constraints:
Consequently, the prevention of hypoglycemia became one of the key indications for rtCGM. Numerous studies demonstrate its effectiveness (HypoDE study [4], IN-CONTROL study [5], GOLD study [6], etc.).
CGM provides a broad set of glucose-related data that enable a much more comprehensive assessment of glucose regulation than SMBG and HbA1c alone.
While HbA1c is still the gold standard for evaluating long-term metabolic control, it has significant limitations:
CGM-generated data significantly expand the possibilities for evaluating and optimizing diabetes therapy.
CGM profile data include:
These parameters can be directly derived from the CGM curves when the device is downloaded using appropriate software.
One of the most important parameters listed above is the percentage of time spent in the target glucose range of 70–180 mg/dL (3.9–10.0 mmol/L)—known as Time in Range (TIR) [7].
Together with HbA1c, TIR reflects the success of diabetes therapy.
An international expert panel derived recommendations for optimal glucose control based on numerous studies across various patient groups. values are summarized in Table SK 1.
Patient groups | Time in the target range (TIR) | Percentage of time spent below (TIR) | Percentage of time above the TIR |
with type 1 and type 2 diabetes | >70% 70-180 mg/dl 3,9-10,0 mmol/l | <4%(70mg/dl;3,9mmol/l) <1%(54mg/dl;3,0mmol/l | Minimizing hypoglycemia |
with type 1 and type 2 diabetes (older, frail) | >70% 70-180 mg/dl 3,9-10,0 mmol/l | <1%(70mg/dl;3,9mmol/l) | >90%(<250 mg/dl;13,9mmol/l) |
Pregnant women with type 1 diabetes | >70% 63-140 mg/dl 3,5-7,8 mmol/l | <4%(63mg/l;3,5mmol/l | <25%(>140mg/dl;7,8mmol/l) |
Pregnant women with type 2 diabetes gestational diabetes
| 63-140 mg/dl 3,5-7,8 mmol/l | (63mg/l;3,5mmol/l | <25%(>140mg/dl;7,8mmol/l) |
Table SK 1: Target values based on CGM data for different groups of people with diabetes, according to the recommendations of an international expert panel [7]
(∆ – exact percentages of time were not defined; further research is needed)
With consistent use, CGM provides a nearly continuous stream of glucose data (288–1440 values per day, depending on the system), allowing a highly detailed assessment of glycemic regulation.
This supports both therapy assistance (SuT and SuP) and therapy control (AID systems).
Even when CGM values are automatically used by therapy algorithms in AID systems, the processing and interpretation of large data volumes via software remain essential. For users, rapid access to data is the priority; for the clinical team, detailed evaluation of therapeutic success is required—possibly as a basis for therapy optimization.
This necessitates software solutions in various formats:
Every CGM system comes with evaluation software that displays glucose profiles and all essential metrics provided by rtCGM. However, when glucose data are presented as individual day-by-day curves, it is often difficult to identify characteristic patterns in glucose regulation.
Historically, daily curves were therefore plotted on top of each other, producing the so-called “spaghetti curves.” Typically, 14 curves from 14 days were superimposed, making interpretation difficult (Fig. SK 8, top).
Ambulatory Glucose Profile (AGP)
For this reason, an international consensus statement recommended displaying CGM data as an Ambulatory Glucose Profile (AGP) [7] (Fig. SK 9, bottom).
From the superimposed raw glucose curves, the AGP displays:
These visual summaries allow rapid conclusions:
The AGP enables 90% reliable statements about glucose patterns [8].
It offers a quick overview that mainly helps generate hypotheses.
By rapidly reviewing consecutive daily profiles, these hypotheses can then be confirmed or rejected [9].
A well-structured guidebook for AGP interpretation, the AGP Manual, is available [10].
In addition to the representation shown in Fig. SK 9, there is another AGP variant in which the light blue (IDR) and dark blue (IQR) bands are color-coded according to glucose levels (Fig. SK 10):
Fig. SK 9: Representation of the original CGM curves over 14 days (top) and the resulting AGP (bottom).
The AGP display illustrates, in a schematic way, how the curves above are processed:
The red arrows indicate declining glucose values on different days, and the green arrow indicates increasing values—each occurring at the same time of day but on different days. These differing daily patterns flatten the overall curve around 8:00 a.m., causing the median in the AGP to appear horizontal in that segment.
However, the IDR band widens at this time, reflecting the underlying variability.
Fig. SK 10: Representation of the AGP in different colors according to glucose levels [10].
The first CGM system was introduced to the market in 1999 (the CGMS by MiniMed). Initially, these systems were blinded CGM systems, meaning that glucose data could only be viewed after removing the sensor and downloading the data to software.
Thus, blinded CGM was used exclusively for diagnostic purposes.
In 2004, the first system displaying real-time glucose values to patients (Guardian RT by MiniMed) became available.
(There had already been a CGM device with glucose display in 2002—the GlucoWatch Biographer by Cygnus—but it failed to gain market acceptance.)
CGM systems that display current glucose values are called real-time CGM (rtCGM).
This finally fulfilled a major patient wish: continuous glucose readings, along with the ability to observe glucose trends.
Since autumn 2016, the costs for CGM systems have been reimbursed by statutory health insurance in Germany, provided appropriate indications exist [11].
[1] Kelly Close Report 21.01.2025
[2] German Federal Ministry of Health: Announcement of a decision of the Federal Joint Committee (G-BA) on an amendment to the directive on methods of outpatient medical care: Continuous interstitial glucose monitoring with real-time devices (rtCGM) for therapy management in patients with insulin-dependent diabetes mellitus, dated 16 June 2016. Federal Gazette, published by the Federal Ministry of Justice and Consumer Protection, 6 September 2016.
[3] Thomas A, Haak T, Tombek A, Kulzer B, Ehrmann D, Kordonouri O, Kroeger J, Schubert-Olesen O, Kolassa R, Siegmund T, Haller N, Heinemann L. Expert discussion on the use of continuous glucose monitoring (CGM) in diabetes management: current status and future perspectives. Diabetologie und Stoffwechsel 2023;18(01):57–68.
[4] Heinemann L, Freckmann G, Ehrmann D, et al. Real-time continuous glucose monitoring in adults with type 1 diabetes and impaired hypoglycemia awareness or severe hypoglycemia treated with MDI (HypoDE). Lancet 2018;391:1367–1377.
[5] van Beers CA, DeVries JH, Kleijer SJ, et al. CGM for patients with type 1 diabetes and impaired awareness of hypoglycemia (IN CONTROL). Lancet Diabetes Endocrinol 2016;4:893–902.
[6] Lind M, Polonsky W, Hirsch IB, et al. Continuous Glucose Monitoring vs Conventional Therapy in Adults With Type 1 Diabetes Using MDI: The GOLD Trial. JAMA 2017;317(4):379–387.
[7] Battelino T, Danne T, Bergenstal RM, et al. Clinical targets for CGM data interpretation: Time in Range (TIR) recommendations. Diabetes Care 2019;42(8):1593–1603.
[8] Dunn TC, Crouther N. Variance assessment of AGP over 3–20 days of CGM. Diabetologia 2010;53(Suppl. 1):S421.
[9] Kröger J, Reichel A, Siegmund T, Ziegler R. Clinical Recommendations for Using AGP. J Diabetes Sci Technol 2020;14(3):586–594.
[10] Kröger J, Reichel A, Siegmund T, Ziegler R. Das Ambulante Glukoseprofil strukturiert auswerten. Kirchheim-Verlag 2018.
[11] Holt RIG, DeVries JH, Hess-Fischl A, et al. The management of type 1 diabetes in adults: ADA–EASD Consensus Report. Diabetologia 2021;64(12):2609–2652.